Banking: how to build financial success with big data?
However, monitoring customer online behaviour and drawing conclusions based on enormous pools of data is a true challenge. What does behavioural targeting look like on an example case?
Bank should adjust its offer to different clients
Let us assume that a bank intends to communicate its new loan product to clients. If only one message is prepared to be shown to all viewers and it’s presented in the same manner to everyone, the effectiveness will be lower than in case of communication tailored to the needs of a particular group. When preparing an offer, one should bear in mind that the bank’s website is the primary source of product information (about the loan). Hence it may prove beneficial to group the clients into “potential”, “seeking” and “decided” ones based on the data gathered in the big data storages.
The potential client doesn’t yet know what he/she wants. They enter the bank’s website without a particular aim, quickly flip through the offer, just to leave the online service shortly after. To propel such internet user to take out a loan, the financial institution’s actions should be mainly focused on prolonging their interest, for example by parading a variety of products available.
The seeking client can be identified by the fact that they visit a bank website more than once, take longer than most other users, clicks on many sub-pages, meticulously browses through the offer, and then seeks further information about the loan on the web. The bank’s interaction with such client should be founded on skilful handling of their attention by providing hints (e.g. links to product pages) and informing them about the possibility to contact a consultant.
Finally, the decided client will hone in on a concrete product, which in this case a loan. If such user comes back to the bank’s website, he/she will browse through those elements (sub-pages and the like) that deal with the loan in question. What’s more, they will devote more of their time to read the content, provide their contact details with a view to interaction with a consultant, and download PDFs with the terms of service, forms to fill in, etc. The bank’s reaction should consist in establishing contact with the client through a staff member, with an aim to finalize the transaction.
Virtual data storages hold genuine potential
As seen above, planning and running a marketing campaign based on analysis of data from big data storages and continuous monitoring of internet users’ actions offer banks a possibility to quickly boost the number of clients, and to strike durable relationships with them. Online activity of a bank entails an array of opportunities when it comes to presentation of the product range and obtaining the desired groups of clients. The knowledge on internet users behaviour is the starting point for any further sales strategy building and adaptation of products to the needs of persons who have identified requirements. Most importantly, however, the awareness of that opportunity should be a part of everyday business decision-making.
